Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
3,481 documents
The note shows how to retrieve Chinese A-share index membership data in BigQuant and filter it for a chosen index. It reads the basic index constituent table, then selects records by the index identifier; an additional filter narrows membership to a…
This brief discussion asks how to translate legacy rolling-factor expressions into SQL: a five-day sum of turnover, a five-day mean of closing prices shifted three days back, and a ten-day statistic. It also raises a practical data-type issue when…
This report summary studies whether mutual funds that performed relatively well continue to do so, and whether weak performers remain weak. It defines persistence through the serial relationship in a fund’s Sharpe ratios: each month, it calculates Sharpe…
The document raises a visualization concern: a smooth backtest equity curve may conceal the size of fluctuations a strategy could experience in practice. It proposes displaying results as daily candles, including each day’s high and low, so readers can see…
This paper proposes a Transformer model for predicting stock price movements, with enhancements intended to capture both local structure and longer-range relationships in financial time series. A multi-scale Gaussian prior is added to encourage the attention…
The document gives a suggested sequence for preparing quantitative factors: remove extreme values, handle missing observations, standardize the data, and then neutralize it. It describes neutralization as removing exposures that can obscure a factor’s…
This report overview argues that commodity price forecasts should combine fundamental and technical analysis. It groups actively traded Chinese commodity futures into five broad sectors—ferrous materials, chemicals, agriculture, nonferrous metals, and…
This trading-rule example explains how to identify stocks that have had exactly one limit-up day during a recent lookback window and then return close to that event day's opening price. The suggested workflow begins with a precomputed limit-up status…
This brief troubleshooting exchange addresses an error encountered when industry features are passed to a shared data-cleaning module for industry neutralization. The reported failure says the industry field is not one-dimensional, but the exchange does not…
This study examines whether firms with predictable quarterly earnings patterns earn unusual stock returns when they announce earnings in their historically strong quarter. It measures seasonality mainly by ranking a firm’s earnings over five years and…
This brief Q&A explains how to trigger a stock purchase on a chosen trading date within a BigQuant strategy’s main function. The suggested method is to read the simulation’s current date and time through the platform’s current-time interface, compare it with…
This investment research summary argues that demand from downstream applications may offer more useful opportunities than broad electronics-sector classifications. It highlights automotive electronics, virtual and augmented reality, defense, industrial and…
The article introduces support as a price area associated with repeated local lows and resistance as an area associated with repeated local highs. It outlines a simple charting workflow: gather price history, use a rolling window to identify local extrema,…
The article argues that greater differences among stocks can improve the opportunity set for systematic equity strategies. When company returns, sectors, and factors diverge, models can rank securities using valuation, momentum, quality, earnings revisions,…
This A-share stock selection example screens for companies meeting three stated criteria: profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below 35. The implementation treats profit growth, return…
This research summary reviews stock-selection factors derived from tick-by-tick trade data, including large-buy share, buy-order concentration, intraday aggressive buying, and informed buying or selling measures. After orthogonalization, the factors…
The document describes a study of four MSCI smart beta equity indexes and a market weighted benchmark. It uses principal component analysis (PCA) to separate shared market movements from strategy specific components, then regresses those components on Fama…
This paper summary describes a reinforcement-learning approach to continuous-time mean-variance portfolio selection. It frames the problem as entropy-regularized relaxed stochastic control, aiming to balance theoretical tractability with practical…
This research note explores whether patent data can reveal links between companies that are missed by industry or supply-chain groupings. It uses shared International Patent Classification information to estimate technological similarity, then tests whether…
This Chinese-language example describes a value-oriented stock selection strategy that refreshes its portfolio every 30 trading days. It selects stocks with positive price-to-book ratios below 1.5 and positive price-to-earnings ratios below 15, provided they…
This research summary reviews a study of how unexpected Federal Reserve policy changes relate to returns across firms with different financing constraints. Using U.S. company and stock data from 1994 to 2007, the study classifies firms by constraint indices…
The article presents a four-stage account of how quantitative traders might exploit retail attention around a fast-rising stock. It describes monitoring public sentiment and trading history to estimate likely stop levels, placing and canceling large pre-open…
The document explains a backtesting context method that checks whether a sell order for a specified security remains unfilled. The method takes the security symbol as its argument and returns a Boolean value indicating whether an order is still awaiting…
This Chinese-language post collects questions about factor research and strategy implementation, but does not provide answers. Topics include adding data factors, scheduling entries and exits, evaluating and combining factors, handling collinearity,…